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Improve test coverage #734
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Working on these unit tests would be a great way to understand this codebase for new engineers |
9 tasks
Coverage checks should include both unit and integration tests. The coverage is much better in that case - 94%, with no file that matters under 70%. You can check this by running
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I see, okay, this makes sense. |
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The test coverage status can be estimated by running
coverage html/xml/report
from the root directory of the project. The below snapshot shows the stats as of July 22, 2024.Improving coverage
While the average test coverage is at 88%, there are source files with coverage as low as 18% (
xrpl/asyncio/ledger/main.py
). These stats include both white-box and black-box testing of the source code. It is desirable to reach a target of 100% test coverage. This should be possible because we don't have platform/architecture-specific code in this library. This task is compatible with the OpenAPI-specification project for Client Libraries. Unit and integration tests can be used to test the machine-generated client libraries.Github Actions
It is useful to have coverage statistics for every pull request, based on their respective
diff
. PR authors can be incentivized to include tests along with their changes. These reports can also be stored on the Codecov platform for future debugging and diagnosis. But, I'm not aware of the cost for the usage of such platforms.The text was updated successfully, but these errors were encountered: